Vast amounts of digital processing can be applied to a communication signal in a digital communications transmitter at low cost. Even a relatively wideband communications signal may be described digitally and processed digitally at great accuracy for a reasonable cost. The digital description of the signal comes from providing a stream of samples at a rate suitable for the bandwidth and at a desired resolution. But the digitally-described-communications signal is nevertheless conventionally converted into an analog form, upconverted, filtered, and amplified for transmission by analog components.
Unlike digital components, analog components achieve only limited accuracy. Moreover, even poor levels of analog accuracy tend to be relatively expensive, and greater accuracy is achieved only at even greater expense. Consequently, a recent trend in digital communications transmitters is to replace analog processing by extending the digital processing as far as possible toward an antenna from which an RF communications signal will be broadcast.
Two other recent trends are the use of modulation forms that require linear amplification and the use of less expensive, but also less accurate, analog components. The modulation forms that require linear amplification are desirable because they allow more information to be conveyed during a given period, over a given bandwidth, and using a given transmission power level. Using less expensive components is always a desirable goal, but it is also an important goal in applications that have mass-market appeal and/or highly competitive markets.
A linear power amplifier is an analog component that is one of the most expensive and also most power-consuming devices in the transmitter. To the extent that a linear power amplifier fails to reproduce and amplify its input signal in a precisely linear manner, signal distortion results. And, as a general rule the distortion worsens as less-expensive and lower-power amplifiers are used.
One type of power-amplifier distortion that has received considerable attention is nonlinearity. Nonlinearity is a particularly prominent characteristic of linear power amplifiers and refers to the extent to which inaccuracy in an amplifier's output signal fails to be linearly related to the amplifier's input signal. Nonlinearity is particularly troublesome in an RF transmitter because it causes spectral regrowth. While an amplifier's RF-input signal may be well-confined in a predetermined portion of the electromagnetic spectrum, any amplifier nonlinearity causes intermodulation so that the amplifier's RF-output signal covers a larger portion of the electromagnetic spectrum.
Transmitters desirably utilize as much of the spectrum as permitted by regulations in order to efficiently convey information. Consequently, spectral regrowth would typically cause a transmitter to be in violation of regulations. To avoid violating regulations, linear power-amplifiers desirably amplify the communications signal they process in as precisely a linear manner as possible. Another trend faced in digital-communications-transmitter designs is that standards and regulations are continually tightening the spectral-regulatory masks within which transmitters must operate. So the need to minimize the spectral-regrowth consequences of power amplifier nonlinearity is greater than ever.
One way to address the spectral-regrowth consequences of power amplifier nonlinearity is to use a higher-power amplifier and operate that higher-power amplifier at a greater backoff. Backoff refers to the degree to which an amplifier is producing a weaker signal than it is capable of producing. Typically, power amplifiers become increasingly linear as they operate further beneath their maximum capabilities, and a greater backoff maintains amplifier operation in the amplifier's more highly linear operating range. Not only does this solution require the use of a more-expensive, higher-power amplifier, but it also usually requires operating the power amplifier in a less efficient operating range, thereby causing the transmitter to consume more power than it might if the amplifier were operated more efficiently. This problem becomes much more pronounced when the communications signal exhibits a high peak-to-average power ratio, such as when several digital communications signals are combined prior to amplification. And, the practice of combining several signals prior to amplification is a common one in cell-site base stations, for example.
Another way to address the consequences of power-amplifier nonlinearity is though digital predistortion. Digital predistortion has been applied to digital communications signals to permit the use of less expensive power amplifiers and also to improve the performance of more expensive power amplifiers. Digital predistortion refers to digital processing applied to a communications signal while it is still in its digital form, prior to analog conversion. The digital processing attempts to distort the digital communications signal in precisely the right way so that after inaccuracies are applied by linear amplification and other analog processing, the resulting communications signal is as precisely accurate as possible. To the extent that amplifier nonlinearity is corrected through digital predistortion, lower-power, less-expensive amplifiers may be used, the amplifiers may be operated at their more-efficient, lower-backoff operating ranges, and spectral regrowth is reduced. And, since the digital predistortion is performed through digital processing, it should be able to implement whatever distortion functions it is instructed to implement in an extremely precise manner and at reasonable cost.
While prior digital predistorting techniques have achieved some successes, those successes have been limited, and the more modern regulatory requirements of tighter spectral-regulatory masks are rendering the conventional predistortion techniques inadequate.
Predistortion techniques require knowledge of the way in which analog components will distort the communications signal in order to craft the proper inverse-predistortion-transfer function that will precisely compensate for distortion introduced by the analog components. The more accurate conventional digital predistortion techniques use a feedback signal derived from the power amplifier output in an attempt to gain this knowledge in real time and to have this knowledge accurately reflect the actual analog components and actual operating conditions.
Conventionally, in response to monitoring this feedback signal, an extensive amount of processing is performed to derive a distortion-transfer function. Then, after deriving the distortion-transfer function, the inverse of the distortion-transfer function is computed and translated into instructions that are programmed into a digital predistorter. In many conventional applications, the transmitter is required to transmit a predetermined sequence of training data to reduce the complexity and improve the accuracy of the extensive processing needed to derive a distortion-transfer function. Less accurate or narrowband conventional predistortion techniques may resort to configuring a digital predistorter as a simple communications-signal filter that is programmed to implement the inverse-transfer-function as best it can. But in many of the more accurate, and usually more expensive, conventional applications, the digital predistorter itself includes one or more look-up-tables whose data serve as the instructions which define the character of the predistortion the digital predistorter will impart to the communications signal.
At the cost of even greater complexity, prior art techniques in high-end applications attempt to compensate for memory effects. In general, memory effects refer to tendencies of power amplifiers to act differently in one set of circumstances than in another. For example, the gain and phase transfer characteristics of a power amplifier may vary as a function of frequency, instantaneous power amplifier bias conditions, temperature, and component aging. In order to address memory effects, predistorter design is typically further complicated by including multiple look-up-tables and extensive processing algorithms to first characterize the memory effects, then derive suitable inverse-transfer functions, and alter predistorter instructions accordingly.
The vast array of conventional predistortion techniques suffers from a variety of problems. The use of training sequences is particularly undesirable because it requires the use of spectrum for control rather than payload purposes, and it typically increases complexity. Generally, increased processing complexity in the path of the feedback signal and in the predistorter design is used to achieve increased accuracy, but only minor improvements in accuracy are achieved at the expense of great increases in processing complexity. Increases in processing complexity for the feedback signal are undesirable because they lead to increased transmitter expense and increased power consumption. Following conventional digital predistortion techniques, the cost of digital predistortion quickly meets or exceeds the cost of using a higher-power amplifier operated at greater backoff to achieve substantially the same result. Thus, digital predistortion has conventionally been practical only in higher-end applications, and even then it has achieved only a limited amount of success.
More specifically, the processing of the feedback signal suffers from some particularly vexing problems using conventional techniques. An inversing operation is conventionally performed to form an inverse-transfer function to use in programming a digital predistorter. While the inversing operation may be somewhat complex on its own, a more serious problem is that it is sensitive to small errors in the feedback signal. Even a small error processed through an inversing operation can result in a significantly inaccurate inverse-transfer function.
Using conventional predistortion techniques, the feedback signal should be captured with great precision and accuracy to precisely and accurately compute the inverse-transfer function. Using conventional techniques, this requires high precision analog-to-digital conversion circuits (A/D) to capture the feedback signal, followed by high resolution, low error, digital circuitry to process the feedback signal. To complicate matters, the feedback signal typically exhibits an expanded bandwidth due to the spectral regrowth caused by power amplifier nonlinearity. To accurately capture the expanded bandwidth of the feedback signal using conventional techniques, the A/D should also consist of high-speed circuits. But such high speed, high-resolution A/D's are often such costly, high-power components that they negate any power amplifier cost savings achievable through digital predistortion in all but the most high-end applications.
In order to avoid the requirement of high-speed, high-resolution A/D's, some conventional predistortion techniques have adopted the practice of processing only the power of the out-of-band portion of the feedback signal. But the power of the out-of-band portion of the feedback signal only indirectly describes analog-component distortion, again causing increased errors and reduced accuracy in inverse-transfer functions.
Even when conventional designs use high-speed, high-resolution A/D's to capture feedback signals, they still fail to control other sources of error that, after an inversion operation, can lead to significant inaccuracy in an inverse-transfer-function. Phase jitter in clocking the A/D adds to error, as does any analog processing that may take place prior to A/D conversion. And, conventional practices call for digital communications signals to be complex signals having in-phase and quadrature components which are conventionally processed separately in the feedback signal prior to A/D conversion. Any quadrature imbalance introduced in the feedback signal by analog processing leads to further error that, after an inversion operation, can cause significant inaccuracy in an inverse-transfer function.
Linear distortion introduced into the communications signal by analog components is believed to be another source of error that plagues conventional digital predistortion techniques. Linear distortion refers to signal inaccuracies that are faithfully reproduced by, or introduced by, the power amplifier and fall in-band. Examples of linear distortion include imbalances of quadrature gain, phase, and group delay. And, as the communication signal becomes more wideband, frequency-dependent gain and phase variances assert a greater linear-distortion influence. Linear distortion is typically viewed as being a more benign form of error than nonlinear distortion because it does not lead to spectral regrowth. Typically, linear distortion is compensated for in a receiver after the transmission channel and the receiver's front-end-analog components have added further linear distortions. But in at least one example, a communication system has been configured so that the receiver determines some linear-distortion-correction parameters that are then communicated back to the transmitter, where the transmitter then implements some corrective action.
The reduction of linear distortion in a transmitted communications signal is desirable because it reduces the amount of linear distortion that a receiver must compensate for in the received signal, which leads to improved performance. And, reduction of linear distortion becomes even more desirable as the communications signal becomes more wideband. But using a receiver to specify the corrective action that a transmitter should take to reduce linear distortion is undesirable because it does not separate channel-induced distortion from transmitter-induced distortion. Since multipath usually asserts a dynamic influence on a transmitted RF communications signal as the signal propagates through a channel, such efforts are usually unsuccessful. In addition, it wastes spectrum for transmitting control data rather than payload data, and it requires a population of receivers to have a compatible capability.
Not only is the failure to address linear distortion in conventional transceivers a problem in its own right, but it is believed to lead to further inaccuracy in characterizing nonlinear transfer functions. Most algorithms which transform raw data into transfer functions are based upon amplifier models that are reasonably accurate under controlled conditions. But the use of linearly-distorted signals to derive transfer functions based upon such models, and particularly over wide bandwidths, can violate the controlled conditions. Consequently, the transfer functions derived therefrom are believed to be less accurate than they might be, and any inverse-transfer functions calculated for use in a digital predistorter can be significantly inaccurate as a result.